1 intro

1.1 Purpose

  1. Validate trialwise ub55 Stroop GLM high-vs-low contrast.
  2. Explore methods of modeling trial-wise parcel-mean beta estimates.

1.2 Notes on analyses

GLMs

  • DMCC55B
  • trialwise LS-A, fix-shaped BLOCK(1,1), Stroop

Contrasts (on regional means):

  • Stroop: \((\text{PC50InCon} + \text{biasInCon} - \text{PC50Con} - \text{biasCon})/2\)

Plotting and statistical details:

2 quick look

2.1 raw data

3 prelim models

3.1 Brains: group-level t-statistics

  • t-values displayed; from HLM fitted to trial-level data (see intro)
  • colors are reversed (black = high, yellow = low) so large positive effects can be seen on white underlay.

3.1.1 Stroop effect: bias stimuli

3.1.2 Stroop effect: PC50 stimuli

3.1.3 Stroop effect: bias+PC50

3.1.4 bias effect: bias - PC50

4 trimmed models

4.1 model QC: outliers

4.2 comparison of effect sizes to untrimmed model

4.3 Examining between-subject variance in stroop (hi/lo) contrast

Top 20 parcels with most btw-subj variance in Stroop effect:

##                   parcel     sddev hemi num.roi
##  1:  LH_DorsAttn_Post_10 0.2202536    L      78
##  2:   LH_DorsAttn_Post_5 0.1823025    L      73
##  3:   LH_DorsAttn_Post_7 0.1700328    L      75
##  4:             LH_Vis_6 0.1621483    L       6
##  5:            RH_Vis_20 0.1589437    R     220
##  6:             RH_Vis_4 0.1508058    R     204
##  7:   LH_DorsAttn_Post_9 0.1501803    L      77
##  8:        LH_Cont_Par_5 0.1487160    L     131
##  9:            LH_Vis_31 0.1456005    L      31
## 10:            RH_Vis_26 0.1436705    R     226
## 11:  RH_DorsAttn_Post_11 0.1422249    R     281
## 12:            RH_Vis_27 0.1416159    R     227
## 13:             RH_Vis_8 0.1413158    R     208
## 14:            RH_Vis_19 0.1411260    R     219
## 15:            RH_Vis_14 0.1350543    R     214
## 16: LH_Default_pCunPCC_5 0.1348901    L     194
## 17:             LH_Vis_9 0.1342421    L       9
## 18:        RH_Cont_Par_6 0.1324992    R     337
## 19:            RH_Vis_30 0.1319830    R     230
## 20:            LH_Vis_21 0.1306674    L      21

Of parcels with significant group-level effect, top 20 parcels with most variance in Stroop effect:

##                   parcel     sddev hemi num.roi
##  1:  LH_DorsAttn_Post_10 0.2202536    L      78
##  2:   LH_DorsAttn_Post_5 0.1823025    L      73
##  3:   LH_DorsAttn_Post_7 0.1700328    L      75
##  4:             LH_Vis_6 0.1621483    L       6
##  5:            RH_Vis_20 0.1589437    R     220
##  6:             RH_Vis_4 0.1508058    R     204
##  7:   LH_DorsAttn_Post_9 0.1501803    L      77
##  8:        LH_Cont_Par_5 0.1487160    L     131
##  9:            LH_Vis_31 0.1456005    L      31
## 10:  RH_DorsAttn_Post_11 0.1422249    R     281
## 11:            RH_Vis_27 0.1416159    R     227
## 12:             RH_Vis_8 0.1413158    R     208
## 13:            RH_Vis_19 0.1411260    R     219
## 14:            RH_Vis_14 0.1350543    R     214
## 15:        RH_Cont_Par_6 0.1324992    R     337
## 16:            RH_Vis_30 0.1319830    R     230
## 17:            LH_Vis_21 0.1306674    L      21
## 18: LH_Default_pCunPCC_1 0.1259369    L     190
## 19:        LH_Cont_Par_1 0.1251313    L     127
## 20:  RH_DorsAttn_Post_10 0.1243004    R     280

4.4 Brains: between-subject variance in stroop (hi/lo) contrast

  • standard deviations of level-two stroop contrasts displayed; from HLM fitted to trial-level data (see intro)
  • colors are reversed (black = high, yellow = low) so large positive effects can be seen on white underlay.

4.4.1 Stroop effect: bias+PC50

5 crossed random effects: subject*item

6 comparison to runwise 1trpk models

6.1 random subject model

6.1.1 scatterplot of parcel-wise estimates

6.1.2 difference maps

6.2 random subject*item model

6.2.1 scatterplot of parcel-wise estimates

6.2.2 difference maps